- While IIoT is gaining momentum, only a small fraction of the world’s Installed Base is connected and monitored remotely.
- While IoT data and analytics will play an increasingly important role in the “health management” of these connected machines, there is nothing comparable for the world’s fleet of unconnected machines.
- But every OEM has huge volumes of data that give a pretty good understanding of what happened to the machine, what inferences can be drawn from this data, and therefore what actions can be taken.
- “Perfect is the enemy of good” – So instead of waiting for IoT data availability, OEMs can start the journey with the data they already have in house.
- The major problem in executing this vision is the inability to scale and make repeatable workflows that create prioritized and refined customer lists that sales, service, and marketing could use to drive action.
- Entytle’s Installed Base Data Platform is a unified, organized, and analyzed data store of all these interactions across millions of installed base machines and is used by OEMs to predict service and sales actions.
IIoT is here to stay.
If anything, 2020 accelerated IoT adoption across the industrial world. What seemed like a B2C wave, definitely seems to be resonating harder with machinery manufacturers.
Industrial IoT is full of paradoxes for Industrials at the moment – on one hand, it is expected to grow into a $950 Billion industry (2019 pre-pandemic estimates) and on the other suffer from a high failure rate. While Microsoft says that 30% of IoT projects, in general, fail at the proof-of-concept stage, Cisco pushes this number much higher at 60%. Cisco goes on to say that just 1 in every 4 organizations considers their IoT initiatives successful.
IIoT, despite all the promises it offers, is still in the ‘early adopter’ stages. Is every equipment or even a large percentage of equipment sold by OEMs connected through IoT today? No.
However, there are strong tailwinds propelling IoT in 2021. Machinery manufacturers are intrinsically slow, steady & exceedingly cautious – IIoT is breaking that mold, forcing Industrials to adopt a new technology at break-neck speed, using trial-and-error, making huge investments into tech that they don’t clearly understand.
IIoT is gaining momentum – but only a small fraction of the world’s installed base is connected and monitored remotely.
A point I made earlier about the slow nature of the Industrial OEMs, needs a little more elaboration. Every machinery manufacturer is simultaneously supporting equipment that was sold 15-20 years ago while designing the next generation of equipment that will become common-place 10 years into the future. IoT isn’t designed for past compatibility. IoT is the shiny new technology that is meant for what is being manufactured today. An air-purifier and an air conditioner sold this year can easily be fitted with the most accurate sensor relaying information back to the manufacturer but the same cannot be achieved easily for an HVAC system that was sold 15 years ago and still needs to be supported.
And that’s another paradox that Industrials have to grapple with when we talk about IoT in the machinery space. IoT’s primary objective is to pre-empt & predict machine performance. While Industrial IoT will do exactly this pre-emption and prediction for the next generation of equipment, what should an Industrial do for the last generation of equipment that will continue to serve, break down, need repairs & services, and the whole aftermarket?
IoT data and analytics will play an increasingly important role in the “health management” of these connected machines, but there is nothing comparable for the world’s fleet of unconnected machines.
So, what’s the single biggest thing that can help Industrial IoT?
I believe, I have safely established that IIoT is a long-term bet for Industrials. A friend of mine from the Industrial world jokingly said that he would be retired before he sees any value coming out of the IIoT project in his company. I found it amusing and yet the brutally honest description of most enterprise projects in our world. ERPs take forever to implement, so why should a large-scale project such as IoT be any different?
So, what should Industrials do in the short run? Here’s a tip – Every OEM has huge volumes of data that gives a pretty good understanding of what happened to the machine, what inferences can be drawn from this data, and therefore what actions can be taken. That data comprises all aspects of their Installed Base.
It resides in multiple tools & silos but it’s very much alive, waiting to be aggregated, cleaned and then analyzed to predict, pre-empt and prescribe a course of action. Use that data, it’s with you right now and will pay off remarkably well (up to 10X of your investment) in an incredibly short span of time (think few months, not quarters or years !!).
“Perfect is the enemy of good” – So instead of waiting for IoT data availability, OEMs can start the journey with the data they already have in house.
The major problem in executing Installed Base vision is an Industrials inability to scale and make repeatable workflows that create prioritized and refined customer lists that sales, service and marketing could use to drive action. This is where an existing, tried and tested technology such as an Installed Base Data Platform can help. Afterall, it’s used by thousands of users across the world’s leading OEMs to achieve exactly that.
Entytle’s Installed Base Data Platform is a unified, organized and analyzed data store of all these interactions across millions of installed base machines and is used by OEMs to predict service and sales actions.